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The Biggest Myth in Spatial Econometrics

42 Pages Posted: 16 Dec 2010  

James P. LeSage

Texas State University - McCoy College of Business Administration

R. Kelley Pace

Louisiana State University - E.J. Ourso College of Business Administration

Date Written: December 1, 2010

Abstract

There is near universal agreement that estimates and inferences from spatial regression models are sensitive to particular specifications used for the spatial weight structure in these models. We find little theoretical basis for this commonly held belief, if estimates and inferences are based on the true partial derivatives for a well-specified spatial regression model. We conclude that this myth may have arisen from past applied work that incorrectly interpreted the model coefficients \emph{as if} they were partial derivatives, or from use of mis-specified models.

Keywords: direct and indirect effects estimates, sensitivity to spatial weights

JEL Classification: C11, C21, C23

Suggested Citation

LeSage, James P. and Pace, R. Kelley, The Biggest Myth in Spatial Econometrics (December 1, 2010). Available at SSRN: https://ssrn.com/abstract=1725503 or http://dx.doi.org/10.2139/ssrn.1725503

James P. LeSage (Contact Author)

Texas State University - McCoy College of Business Administration ( email )

Finanace and Economics Department
601 University Drive
San Marcos, TX 78666
United States
512-245-0256 (Phone)
512-245-3089 (Fax)

HOME PAGE: http://www.spatial-econometrics.com

R. Kelley Pace

Louisiana State University - E.J. Ourso College of Business Administration ( email )

Department of Finance
2164 B Patrick F. Taylor Hall
Baton Rouge, LA 70803-6308
United States
(225)-578-6256 (Phone)
(225)-578-9065 (Fax)

HOME PAGE: http://www.spatial-statistics.com

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